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transformerlm-flow-mnist
trixyL/transformerlm-flow-mnist
transformerlm-flow-mnist is a machine learning model from trixyL. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
Training run artifacts from https://github.com/triloy8/transformerlm: a minimal flow-matching DiT-style image model trained on MNIST with a fixed 784-token context (28×28 image values) and conditional generation using…
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Updated Mar 8, 2026
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Mar 8, 2026
- Updated
- Mar 8, 2026
- SHA
- 0c9af022
Datasets
Model card
From the Hugging Face model README
🧠🌊 TransformerLM (Flow 784, 256) — MNIST
Training run artifacts from https://github.com/triloy8/transformerlm: a minimal flow-matching DiT-style image model trained on MNIST with a fixed 784-token context (28×28 image values) and conditional generation using discrete labels plus a null label for classifier-free guidance (CFG).
✅ Key Facts
- Model type:
image_ditflow-matching Transformer - Objective: Flow matching
- Dataset: MNIST (full 8-bit pixel values, 256 levels)
- Context length: 784 values (28×28 image)
- Layers: 8
- Heads: 16
- d_model: 256
- d_ff: 1024
- Training setup: Single NVIDIA A40 (48GB)
- Runtime: ~3 hours ⏱️
📦 What’s Inside
- 8k steps (full run), including:
- Optimizer state
- RNG state
- Safetensors weights
- Run config
- Best checkpoint alias (
v007000) - Latest checkpoint alias (
v008000)
🚀 Reproducibility
Exact commit that launched the run: https://github.com/triloy8/transformerlm/commit/01459662f08e83abc997966415d648563860859e
- License
- apache-2.0
- Languages
- en
- Created
- Mar 8, 2026
- Updated
- Mar 8, 2026